What is he best known for?
The fields of study he is best known for:
- Software
- Operating system
- Programming language
His primary scientific interests are in Software, Software engineering, Software quality, Software maintenance and Empirical research.
His Software study combines topics from a wide range of disciplines, such as Data mining and Source code.
The Source code study which covers Data science that intersects with Process.
Bram Adams integrates many fields, such as Software engineering and Context, in his works.
His work deals with themes such as Software bug and Android, which intersect with Software quality.
His Software maintenance research focuses on Dimension and how it connects with Decision tree.
His most cited work include:
- A large-scale empirical study of just-in-time quality assurance (266 citations)
- The impact of code review coverage and code review participation on software quality: a case study of the qt, VTK, and ITK projects (171 citations)
- An empirical study of the impact of modern code review practices on software quality (130 citations)
What are the main themes of his work throughout his whole career to date?
Bram Adams mostly deals with Software, Software engineering, Source code, Empirical research and World Wide Web.
His Software research is multidisciplinary, incorporating perspectives in Database, Data science and Code.
His studies deal with areas such as Software system, Software maintenance, Software build and Software development as well as Software engineering.
His Source code study integrates concerns from other disciplines, such as Code refactoring, Information retrieval, KPI-driven code analysis and Software evolution.
Mobile device is closely connected to Android in his research, which is encompassed under the umbrella topic of World Wide Web.
His work carried out in the field of Software quality brings together such families of science as Quality and Software development process.
He most often published in these fields:
- Software (39.83%)
- Software engineering (35.50%)
- Source code (18.18%)
What were the highlights of his more recent work (between 2017-2021)?
- Software (39.83%)
- Empirical research (16.45%)
- Artificial intelligence (4.33%)
In recent papers he was focusing on the following fields of study:
Bram Adams mainly investigates Software, Empirical research, Artificial intelligence, Software engineering and Data science.
His work in the fields of Software, such as Software bug, intersects with other areas such as Productivity.
His Artificial intelligence research incorporates themes from Machine learning, Open/closed principle and Process.
His studies in Software engineering integrate themes in fields like Software system, Compiler and Feature.
His Data science research includes elements of Release engineering and Software repository.
His work in Open source addresses subjects such as Cross-platform, which are connected to disciplines such as World Wide Web.
Between 2017 and 2021, his most popular works were:
- Software Engineering for Machine-Learning Applications: The Road Ahead (32 citations)
- An exploratory qualitative and quantitative analysis of emotions in issue report comments of open source systems (28 citations)
- Software Configuration Engineering in Practice Interviews, Survey, and Systematic Literature Review (16 citations)
In his most recent research, the most cited papers focused on:
- Software
- Operating system
- Programming language
The scientist’s investigation covers issues in Software, Software system, Source code, Software engineering and Key.
His study looks at the relationship between Software and fields such as Data science, as well as how they intersect with chemical problems.
His Software system research is multidisciplinary, relying on both Java, Java Native Interface, Constant and Software quality.
The various areas that he examines in his Source code study include Source lines of code, Data mining, Linux kernel and Commit.
He has researched Software engineering in several fields, including Compiler, Software development and Feature.
His Key research integrates issues from Reliability, Swarm behaviour, Robustness, Artificial intelligence and Theme.
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